www.uhasselt.be
DSpace

Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16138

Title: Synthetic Population Techniques in Activity-Based Research
Authors: CHO, Sungjin
BELLEMANS, Tom
CREEMERS, Lieve
KNAPEN, Luk
JANSSENS, Davy
WETS, Geert
Issue Date: 2014
Citation: Data on Science and Simulation in Transportation Research, p. 48-70
Series/Report: Advances in Data Mining and Database Management (ADMDM) Book Series
Abstract: Activity-based approach, which aims to estimate an individual induced traffic demand derived from activities, has been applied for traffic demand forecast research. The activity-based approach normally uses two types of input data: daily activity-trip schedule and population data, as well as environment information. In general, it seems hard to use those data because of privacy protection and expense. Therefore, it is indispensable to find an alternative source to population data. A synthetic population technique provides a solution to this problem. Previous research has already developed a few techniques for generating a synthetic population (e.g. IPF [Iterative Proportional Fitting] and CO [Combinatorial Optimization]), and the synthetic population techniques have been applied for the activity-based research in transportation. However, using those techniques is not easy for non-expert researchers not only due to the fact that there are no explicit terminologies and concrete solutions to existing issues, but also every synthetic population technique uses different types of data. In this sense, this chapter provides a potential reader with a guideline for using the synthetic population techniques by introducing terminologies, related research, and giving an account for the working process to create a synthetic population for Flanders in Belgium, problematic issues, and solutions.
URI: http://hdl.handle.net/1942/16138
Link to publication: http://www.igi-global.com/book/data-science-simulation-transportation-research/78944#author-editor-biography
DOI: 10.4018/978-1-4666-4920-0.ch003
ISI #: 000364530200005
ISBN: 9781466649200
Category: B2
Type: Book Section
Validation: vabb, 2017
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
N/A5.96 MBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.